Group 18: R for Bio Data Science final project

Kacper
Maciejewski
(s243548)
Sofia
Russo
(s252054)
Aleksandra
Wozniak
(s253713)
Gabriel
Loayza
(s252608)
Dagmar
Geevers
(s252256)

Introduction

Epigenetic modifiers HDAC

  • HDAC gene family: epigenetic modifiers that remove histone acetyl groups and repress gene expression

  • Cancer stemness: HDACs are often overexpressed in tumors and help maintain cancer stem cells and therapy resistance

  • Immunogenicity: HDAC activity can reduce antigen presentation and promote an immunosuppressive tumor microenvironment

  • Therapeutic angle: HDAC inhibitors can decrease cancer stemness and increase tumor immunogenicity, improving responses to immunotherapy

Baretti and Yarchoan (2021), Maciejewski et al. (2024)

HDACs as drugs

hdac
Gupta (2025)

Introduction

Project aim

WHAT: Is HDAC gene family expression related to cancer stemness, clinical outcome, and survival?

HOW: By recreating the visualizations and analyses provided in the Maciejewski et al. (2024) study suing the same data and our own R implementations.

WHY: To confirm the correctness of conclusions in the given paper as there is little-to-none literature confirming their findings so far.

Methods

Analysis - project overview

flowchart TD
  A[cBioPortal] --> B[TCGA clinical data]
  A --> C[TCGA expression data]

  %% Malta et al. before mRNAsi
  X[Malta et al. study] --> D[mRNAsi stemness index]

  %% Data cleanup after B, C, and D
  B --> Bclean[Data cleanup]
  C --> Cclean[Data cleanup]
  D --> Dclean[Data cleanup]

  %% Data merge (data join)
  Bclean --> DM[Data merge]
  Cclean --> DM
  Dclean --> DM

  %% After data merge: data augmentation
  DM --> E[Data augmentation]

  E --> F[Descriptive summary]

  E --> G[Correlation analysis]
  G --> H[mRNAsi]
  G --> I[stage/grade]

  E --> J[Survival modeling]
  J --> K[Overall Survival]
  J --> L[Disease Free Survival]
  
  F --> M[Plots & tables]
  H --> M
  I --> M
  K --> M
  L --> M

  %% Styling: white background, black text
  style A fill:#ffffff,stroke:#000000,color:#000000
  style B fill:#ffffff,stroke:#000000,color:#000000
  style C fill:#ffffff,stroke:#000000,color:#000000
  style X fill:#ffffff,stroke:#000000,color:#000000
  style D fill:#ffffff,stroke:#000000,color:#000000
  style Bclean fill:#ffffff,stroke:#000000,color:#000000
  style Cclean fill:#ffffff,stroke:#000000,color:#000000
  style Dclean fill:#ffffff,stroke:#000000,color:#000000
  style DM fill:#ffffff,stroke:#000000,color:#000000
  style E fill:#ffffff,stroke:#000000,color:#000000
  style F fill:#ffffff,stroke:#000000,color:#000000
  style G fill:#ffffff,stroke:#000000,color:#000000
  style H fill:#ffffff,stroke:#000000,color:#000000
  style I fill:#ffffff,stroke:#000000,color:#000000
  style J fill:#ffffff,stroke:#000000,color:#000000
  style K fill:#ffffff,stroke:#000000,color:#000000
  style L fill:#ffffff,stroke:#000000,color:#000000
  style M fill:#ffffff,stroke:#000000,color:#000000

  • Spearman correlations with P-value correction for multiple testing (BH method)
  • Cox-based risk prediction model with high (Q3, 75th percentile) relative to low (Q1, 25th percentile) expression of specific HDAC family member

Methods

Data

mrnasi

mrnasi

mrnasi

Results

The Expression of HDAC Family Members Is Associated with Clinicopathological Features of TCGA Solid Tumors in a Cancer-Dependent and Gene-Specific Manner

HDAC expression vs grade

grade

HDAC expression vs stage

stage

Results

HDAC family expression is associted with survival

![](../results/07_plot_Disease_Free_Survival.png

HDAC gene expression does not show consistent behaviour within HDAC families. The prognostic relevance is highly tumor-dependent but still present.

Results

Class I HDAC Family Members Correlate Positively, While Class IIA HDAC Genes Correlate Negatively with Cancer Stemness across TCGA Solid Tumors

  • Class I HDAC family members correlate positively, while class IIA HDAC genes correlate negatively with cancer stemness across TCGA solid tumors.
  • Specifically, HDAC2 (member of class I) and HDAC7 (member of class IIA) genes show the highest correlations across studied solid tumors, exhibiting statistically significant opposite trends

mrnasi

Discussion

Inverse association with cancer stemness and immunogenicity

  • This project confirmed a significant association between cancer stemness and an elevated expression of class I HDAC family members, especially HDAC2, where the association was robust and universal regardless of the tested tumor type. On the other hand, the relation of class IIA HDAC members is significantly negative, with HDAC7 exhibiting the strongest ones

Discussion

Technical take aways

  • We successful managed to recreate expected figures and managed to derive exactly the same results and conclusions.
  • In our future project we should use try(..., silent=TRUE) with higher caution as it made it hard for us to debug.

Further steps and improvements

  • Confirming the relation of HDAC and immunological inflamation which was included in the reproduced paper but outside of the scope of this project.
  • Plotting function could have been shared across all figures to deliver the same aesthetics.
  • pheatmap or complexheatmap would create better-looking plots but we wanted to be 100% aligned with the course content.

References

Baretti, Marina, and Mark Yarchoan. 2021. “Epigenetic Modifiers Synergize with Immune-Checkpoint Blockade to Enhance Long-Lasting Antitumor Efficacy.” The Journal of Clinical Investigation 131 (16): e151002. https://doi.org/10.1172/JCI151002.
Gupta, Preeti. 2025. “Epigenetic Alterations in Cancer: The Therapeutic Potential of Epigenetic Drugs in Cancer Therapy.” Drugs and Drug Candidates 4 (2): 15. https://doi.org/10.3390/ddc4020015.
Maciejewski, Kacper, Marek Giers, Urszula Oleksiewicz, and Patrycja Czerwinska. 2024. “The Epigenetic Modifiers HDAC2 and HDAC7 Inversely Associate with Cancer Stemness and Immunity in Solid Tumors.” International Journal of Molecular Sciences 25 (14): 7841. https://doi.org/10.3390/ijms25147841.